On adaptive estimation in partial linear models
Georgi Golubev and
Wolfgang Härdle ()
No 2000,21, SFB 373 Discussion Papers from Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes
We consider a problem of estimation of parametric component in a partial linear model. Suppose that a finite set E of linear estimators is given. Our goal is to mimic the estimator in E that has the smallest risk. Using a second order expansion of the risk of linear estimators we propose a practically feasible adaptive procedure for choke of smoothing parameters based on the principle of unbiased risk estimation.
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Working Paper: On adaptive estimation in partial linear models (1997)
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Persistent link: https://EconPapers.repec.org/RePEc:zbw:sfb373:200021
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